AI Solutions Engineer

AI Solutions Engineer

Contract or Contract-to-Hire

100% REMOTE

Interview Process: 2 rounds; virtual

W2 Only

Person should have very deep Healthcare & EPIC domain expertise along with hands on experience working on AI technology.

More than having certifications, candidate must have recent working experience on EPIC technologies. Preferred cert

AI solutions requires deep knowledge of Epic and also most of the AI solutions needs to be integrated within EPIC for seamless user experience

Description:

Follows company software development lifecycle to design, code, configure, test, debug, and document system and application programs. Assists in preparing technical design specifications based on functional requirements and analysis documents. Reviews functional requirements, analysis and design documents and provides feedback. Collaborates with other development staff to achieve quality and consistency. Participates in architecture, design and code reviews. Develops and maintains operational and system level documentation.

Years Experience: 10+.

Experience: Relies on extensive experience to plan and accomplish tasks. Leadership/Contributions: May lead multiple layers of resources.

Reports to: Director or VP.

Advanced Degree or Certifications: Yes, highest possible. Epic Certification would be a top qualification.

Top qualifications:

• Architecture & System Design: Design scalable, secure, resilient cloud applications with a strong understanding of distributed systems, APIs, microservices, integration patterns, and software architecture fundamentals.
• Healthcare domain expertise. Recent experience on Healthcare and EHR specifically Epic. Epic certified
• Cloud Architecture: Deep experience designing and implementing cloud solutions, preferably Microsoft Azure. Experience with AWS or Google Cloud Platform is also valuable.
• Infrastructure as Code: Strong experience with Infrastructure as Code and cloud provisioning using technologies such as Bicep, Terraform, ARM, or equivalent tools.
• Software Engineering & Git: Strong software engineering fundamentals and a deep understanding of Git, branching strategies, pull requests, code reviews, versioning, and collaborative development practices.
• CI/CD & DevOps: Design and implement automated CI/CD pipelines using Azure DevOps, GitHub Actions, GitLab, Jenkins, or similar platforms, with an emphasis on automated, repeatable, and reliable software delivery.
• Containers & Cloud-Native Platforms: Hands-on experience with Docker and Kubernetes, including containerized application architecture, deployment, scaling, networking, and operational considerations.
• Data & Application Platforms: Strong experience with relational and distributed data technologies such as PostgreSQL, MySQL, Redis, and Databricks, with an understanding of data architecture, performance, scalability, and integration.
• Observability, Security & Production Operations: Design systems for production from the start, with strong understanding of observability, application performance, logging, metrics, tracing, alerting, security, and operational resilience. Experience with technologies such as Grafana, Azure Application Insights, Azure Log Analytics, OpenTelemetry (OTel), or similar platforms is preferred. Understand how to diagnose, monitor, secure, and operate distributed systems in production.
• Generative AI & AI-Assisted Development: Actively leverage GenAI tools to accelerate coding, testing, documentation, troubleshooting, and solution development. Experience building or integrating GenAI-powered applications is strongly preferred. AI should be used as a productivity multiplier not a substitute for engineering judgment, architectural thinking, or technical ownership.
• Product & Technical Ownership: Maintain end-to-end ownership of the products and systems you architect. Balance AI-assisted development speed with sound engineering practices, security, scalability, maintainability, and overall product outcomes. Be comfortable moving between high-level architecture and hands-on implementation when needed.